This document compares Apache Kafka and AWS Kinesis for message streaming. It outlines that Kafka is an open source publish-subscribe messaging system designed as a distributed commit log, while Kinesis provides streaming data services. It also notes some key differences like Kafka typically handling over 8000 messages/second while Kinesis can handle under 100 messages/second.
This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses exactly once semantics in Apache Kafka 0.11. It provides an overview of how Kafka achieved exactly once delivery between producers and consumers. Key points include:
- Kafka 0.11 introduced exactly once semantics with changes to support transactions and deduplication.
- Producers can write in a transactional fashion and receive acknowledgments of committed writes from brokers.
- Brokers store commit markers to track the progress of transactions and ensure no data loss during failures.
- Consumers can read from brokers in a transactional mode and receive data only from committed transactions, guaranteeing no duplication of records.
- This allows reliable message delivery semantics between producers and consumers with Kafka acting as
This document compares Apache Kafka and AWS Kinesis for message streaming. It outlines that Kafka is an open source publish-subscribe messaging system designed as a distributed commit log, while Kinesis provides streaming data services. It also notes some key differences like Kafka typically handling over 8000 messages/second while Kinesis can handle under 100 messages/second.
This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses exactly once semantics in Apache Kafka 0.11. It provides an overview of how Kafka achieved exactly once delivery between producers and consumers. Key points include:
- Kafka 0.11 introduced exactly once semantics with changes to support transactions and deduplication.
- Producers can write in a transactional fashion and receive acknowledgments of committed writes from brokers.
- Brokers store commit markers to track the progress of transactions and ensure no data loss during failures.
- Consumers can read from brokers in a transactional mode and receive data only from committed transactions, guaranteeing no duplication of records.
- This allows reliable message delivery semantics between producers and consumers with Kafka acting as
This document provides an overview and summary of a presentation about authentication and authorization for cloud native applications using Keycloak. The presentation introduces Keycloak as an open source identity and access management solution, discusses the importance of authentication and authorization, and describes how Keycloak can be used for authentication methods like single sign-on, social login, and multi-factor authentication as well as authorization standards like OAuth 2.0 and Financial-Grade API 1.0. It also covers Keycloak features that help secure cloud native environments and applications.
The document discusses the challenge of implementing scalable authorization and describes how to use Keycloak's authorization service to achieve it. Keycloak allows defining fine-grained authorization policies and centralizing authorization data, improving scalability. Combined with OPA and CockroachDB, Keycloak can also enhance performance and availability while maintaining a centralized approach. The document provides an overview of Keycloak's authorization capabilities and how they enable scalable and standards-based authorization.
The document describes a session from the KubeCon EU 2023 conference on Keycloak, an open-source identity and access management solution. It provides an overview of the session which was presented by Alexander Schwartz from Red Hat and Yuuichi Nakamura from Hitachi and demonstrated how Keycloak can be used to securely authenticate users to applications like Grafana. It also discusses Keycloak's support for advanced security specifications like FAPI and efforts by the FAPI-SIG working group to promote features needed for compliance.
This document discusses security considerations for API gateway aggregation. It proposes building an API gateway aggregator in front of existing API gateways to expose APIs outside a company while minimizing security risks and impact on existing services. It describes how the aggregator can implement OAuth 2.0 authorization with a centralized authorization server and token exchange to authorize external applications without complexifying authorization for internal services. Advanced use cases discussed include supporting the Financial-grade API security profile for highly sensitive data and implementing zero-trust networking.
This document discusses the differences between assertion-based access tokens and handle-based access tokens in OAuth 2.0. Assertion-based tokens are parsable tokens like JWTs that contain user and client information, while handle-based tokens are opaque references. Assertion-based tokens have advantages for performance and scalability but require cryptographic protection, while handle-based tokens require validation through the authorization server. The document then examines scenarios where handle-based tokens could cause problems, such as with multiple authorization servers, and outlines secure validation steps for assertion-based tokens.
Yoshiyuki Tabata from Hitachi presented on API specifications and tools that help engineers construct high-security API systems. He discussed standards like OAuth 2.0, OIDC, PKCE, and OAuth MTLS. Useful features for testing include decoding tokens to check validity, and calling authorization server endpoints to validate access control. Implementing these features in mock servers and clients allows engineers to efficiently test if high-security requirements are met before production.
The document discusses implementing security and availability requirements for a banking API system using open source software. It describes using the 3scale API management platform and Keycloak identity management software together to meet authentication, authorization, access control, availability, and standards compliance requirements. Patches were submitted to these open source projects to enhance their features and better support the banking use case.
This document discusses implementing a lightweight zero-trust network using the open source tools Keycloak and NGINX. It begins by explaining the transition from a traditional network security model with clear boundaries between public and private networks to a zero-trust model where security boundaries are defined individually for each service or pod. It then covers how to implement the underlying technologies of JWT validation, mutual TLS authentication, and OAuth MTLS using Keycloak as an authorization server and NGINX as an API gateway. Additional topics discussed include how to secure east-west internal traffic and resolve potential policy decision point chokepoints.
This document discusses identity provider mix-up attacks in OAuth and describes several patterns of these attacks. It also outlines various mitigations and which mitigations are effective against each attack pattern. Specifically, it covers attack patterns that occur before and after the authorization code is obtained, listing three patterns for the former and two for the latter. Finally, it analyzes how the mitigation of using distinct redirect URIs matches up against each combination of attack patterns.